Gaussian Processes papers, 2023–2026

Key findings

• Gaussian Processes went from 154 papers in 2023 to 341 in 2026, roughly 2.2x in three years.
• NeurIPS publishes the most Gaussian Processes work: 372 papers from 2023 to 2026, 35% of the four-venue total.
• The fastest-growing overlap is with 3D Vision: papers tagged with both rose from 0 in 2023 to 158 in 2026.
• Among the 5 topics under Probabilistic and Bayesian, it ranks #1 by 2026 paper count; the fastest grower in the group, Generative Flows, is up 1.9x versus 2.2x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026Adaptive Prior Selection in Gaussian Process Bandits with Thompson Sampling
• ICML 2026A unified theory of feature learning in RNNs and DNNs
• ICLR 2026Adaptive Gaussian Expansion for On-the-fly Category Discovery
• CVPR 2026Distilling Unsigned Distance Function for Surface Reconstruction from 3D Gaussian
• NeurIPS 2025Accelerated Evolving Set Processes for Local PageRank Computation
• ICML 2025BARK: A Fully Bayesian Tree Kernel for Black-box Optimization
• ICLR 2025Boosting Methods for Interval-censored Data with Regression and Classification
• CVPR 20253D Gaussian Head Avatars with Expressive Dynamic Appearances by Compact Tensorial Representations
• NeurIPS 2024Numerically Stable Sparse Gaussian Processes via Minimum Separation using Cover Trees
• ICML 2024A Rate-Distortion View of Uncertainty Quantification
• ICLR 2024A General Framework for User-Guided Bayesian Optimization
• CVPR 2024Deep Imbalanced Regression via Hierarchical Classification Adjustment
• NeurIPS 2023A Bayesian Take on Gaussian Process Networks
• ICML 2023Are Gaussian Data All You Need? The Extents and Limits of Universality in High-Dimensional Generalized Linear Estimation
• ICLR 2023Accurate Bayesian Meta-Learning by Accurate Task Posterior Inference
• CVPR 2023Robust and Scalable Gaussian Process Regression and Its Applications
• NeurIPS 2026Amortized Structured Stochastic Variational Inference for Gaussian Process Latent Variable Models
• ICML 2026ALAS: Additive Learnable Alpha-Stable Kernels for Flexible Bayesian Optimization
• ICLR 2026Continuous multinomial logistic regression for neural decoding
• CVPR 2026ELITE Efficient Gaussian Head Avatar from a Monocular Video via

All Gaussian Processes papers

323 papers, page 4 of 7

151. ICLR 2025Optimal Non-Asymptotic Rates of Value Iteration for Average-Reward Markov Decision Processes
152. ICLR 2025Optimistic Games for Combinatorial Bayesian Optimization with Application to Protein Design
153. ICLR 2025Poison-splat: Computation Cost Attack on 3D Gaussian Splatting
154. ICLR 2025ReMatching Dynamic Reconstruction Flow
155. ICLR 2025Residual Deep Gaussian Processes on Manifolds
156. ICLR 2025Robust Simulation-Based Inference under Missing Data via Neural Processes
157. ICLR 2025SecureGS: Boosting the Security and Fidelity of 3D Gaussian Splatting Steganography
158. ICLR 2025Signature Kernel Conditional Independence Tests in Causal Discovery for Stochastic Processes
159. ICLR 2025Standard Gaussian Process is All You Need for High-Dimensional Bayesian Optimization
160. ICLR 2025Stochastic variance-reduced Gaussian variational inference on the Bures-Wasserstein manifold
161. ICLR 2025SurFhead: Affine Rig Blending for Geometrically Accurate 2D Gaussian Surfel Head Avatars
162. ICLR 2025The Breakdown of Gaussian Universality in Classification of High-dimensional Linear Factor Mixtures
163. ICLR 2025Unlocking Point Processes through Point Set Diffusion
164. ICLR 2025Variance-Reducing Couplings for Random Features
165. ICML 2025Adjusting Model Size in Continual Gaussian Processes: How Big is Big Enough?
166. ICML 2025BARK: A Fully Bayesian Tree Kernel for Black-box Optimization
167. ICML 2025Bayesian Basis Function Approximation for Scalable Gaussian Process Priors in Deep Generative Models
168. ICML 2025Determinant Estimation under Memory Constraints and Neural Scaling Laws
169. ICML 2025Diffusion models for Gaussian distributions: Exact solutions and Wasserstein errors
170. ICML 2025Distributionally Robust Active Learning for Gaussian Process Regression
171. ICML 2025Exact Recovery of Sparse Binary Vectors from Generalized Linear Measurements
172. ICML 2025Feature learning from non-Gaussian inputs: the case of Independent Component Analysis in high dimensions
173. ICML 2025Finite-Time Analysis of Discrete-Time Stochastic Interpolants
174. ICML 2025Fully Heteroscedastic Count Regression with Deep Double Poisson Networks
175. ICML 2025Global Optimization with a Power-Transformed Objective and Gaussian Smoothing
176. ICML 2025Global-Local Dirichlet Processes for Clustering Grouped Data in the Presence of Group-Specific Idiosyncratic Variables
177. ICML 2025Gradient Flow Provably Learns Robust Classifiers for Orthonormal GMMs
178. ICML 2025Graph Neural Network Generalization With Gaussian Mixture Model Based Augmentation
179. ICML 2025Gridded Transformer Neural Processes for Spatio-Temporal Data
180. ICML 2025Improved Regret Analysis in Gaussian Process Bandits: Optimality for Noiseless Reward, RKHS norm, and Non-Stationary Variance
181. ICML 2025Integration-free Kernels for Equivariant Gaussian Process Modelling
182. ICML 2025Interaction-Aware Gaussian Weighting for Clustered Federated Learning
183. ICML 2025K$^2$IE: Kernel Method-based Kernel Intensity Estimators for Inhomogeneous Poisson Processes
184. ICML 2025Laplace Transform Based Low-Complexity Learning of Continuous Markov Semigroups
185. ICML 2025Learning Gaussian DAG Models without Condition Number Bounds
186. ICML 2025Learning multivariate Gaussians with imperfect advice
187. ICML 2025Learning Robust Neural Processes with Risk-Averse Stochastic Optimization
188. ICML 2025Learning Safe Control via On-the-Fly Bandit Exploration
189. ICML 2025Learning Time-Varying Multi-Region Brain Communications via Scalable Markovian Gaussian Processes
190. ICML 2025Learning Utilities from Demonstrations in Markov Decision Processes
191. ICML 2025Linearization Turns Neural Operators into Function-Valued Gaussian Processes
192. ICML 2025Low-Rank Thinning
193. ICML 2025Model-Based Exploration in Monitored Markov Decision Processes
194. ICML 2025Neighbour-Driven Gaussian Process Variational Autoencoders for Scalable Structured Latent Modelling
195. ICML 2025New Bounds for Sparse Variational Gaussian Processes
196. ICML 2025On the Training Convergence of Transformers for In-Context Classification of Gaussian Mixtures
197. ICML 2025PAC-Bayes Analysis for Recalibration in Classification
198. ICML 2025Pareto-frontier Entropy Search with Variational Lower Bound Maximization
199. ICML 2025PF3plat: Pose-Free Feed-Forward 3D Gaussian Splatting for Novel View Synthesis
200. ICML 2025PRIME: Deep Imbalanced Regression with Proxies

FAQ

How many Gaussian Processes papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

1,049 in total: 154 in 2023, 231 in 2024, 323 in 2025, 341 in 2026.

How many Gaussian Processes papers are at NeurIPS 2026?

NeurIPS 2026 has 106 Gaussian Processes papers, versus 106 the year before.

How many Gaussian Processes papers are at ICLR 2026?

ICLR 2026 has 40 Gaussian Processes papers, versus 41 the year before.

How many Gaussian Processes papers are at ICML 2026?

ICML 2026 has 79 Gaussian Processes papers, versus 53 the year before.

How many Gaussian Processes papers are at CVPR 2026?

CVPR 2026 has 116 Gaussian Processes papers, versus 123 the year before.

Which conference publishes the most Gaussian Processes papers?

NeurIPS, with 372 papers from 2023 to 2026.